The Dataquest Download
Level up your data and AI skills, one newsletter at a time.
Hello, Dataquesters!
Here’s what we have for you in this edition:
Top Read: Get hands-on with MongoDB and see how NoSQL databases handle fast-changing requirements—perfect for modern apps that outgrow traditional SQL. Read the tutorial
Community Highlights: A deep-learning model for IPO gains, a motivating career story and Q&A, polished portfolios, practical project advice, and tips on Power BI and Python coding. Join the discussion
DQ Resources: Build and deploy your own AI chatbot with Python, then take it further by designing a Streamlit web interface for real-world use. Try the project
What We’re Reading: Creative optimization with generative art, cleaner code with Python’s functools, and how AI is shaping new roles in coding. Learn more
SQL databases work well—until your data model starts changing faster than your schema can keep up. That’s the challenge growing companies face, and it’s exactly where NoSQL databases like MongoDB shine.
In this tutorial, you’ll get hands-on experience building a real-world review system in MongoDB. You’ll see how document databases handle evolving requirements, like photos, video reviews, and badges without endless schema migrations. By the end, you’ll understand why MongoDB powers companies from startups to Fortune 500s, and how to use it in your own projects.
From the Community
Predicting Listing Gains in the Indian IPO Market Using TensorFlow: Steve analyzed an IPO listing-gains dataset to build a deep-learning classification model. He produced a professional report with compelling visualizations, clean code, and strong emphasis on explaining every key decision along the way.
Success Story and Invitation to a Discussion: Qi shared a detailed account of his path into data science and his highly motivational learning journey, which led to rapid professional growth and remarkable career success. If you want to thrive in data science, join the discussion.
Data Scientist Project Portfolio: Israel posted his exemplary project portfolio, showcasing his solid mastery of a wide range of modern technologies, including Python, SQL, Power BI, Tableau, and Excel.
Building Dataquest Guided Projects the Right Way: Artur discusses the importance of starting with guided projects before attempting independent ones. He offers actionable suggestions to help your projects shine and truly stand out from the crowd.
Power BI Is More Than Just a Visualization Tool: Pranta dispels the common myth that Power BI is only for data visualization. He explains that it’s a complete Business Intelligence ecosystem with capabilities for data preparation, data modeling, data visualization, and secure project collaboration.
Using Python Superclass Functions: Hamza breaks down the lesser-known concept of superclass functions in Python and provides a simple code example illustrating how they work. This approach is particularly handy for reusing and organizing code.
DQ Resources
Build a Web Interface for Your Chatbot with Streamlit: Learn how to transform a command-line chatbot into a professional web app using Streamlit. This hands-on tutorial shows you how to add interactive controls, customizable personalities, and deploy your chatbot online, all without HTML, CSS, or JavaScript. By the end, you’ll have a deployed web app that demonstrates your AI and user-facing development skills.
Build an AI Chatbot with Python and the OpenAI API: A hands-on tutorial that shows you how to build a fully functional chatbot from scratch in Python. You’ll learn to manage conversations, control costs with token budgeting, and design custom AI personalities that persist across exchanges. By the end, you’ll have both a working chatbot and the foundational skills to create more advanced AI applications.
What We're Reading
Learning Optimization with Generative Art: A creative exploration of the simplex method as a personal project. The author blends optimization algorithms with generative art, turning abstract math concepts into beautiful algorithmic patterns.
Level Up with functools in Python: Many devs repeat logic without realizing it—this article shows how functools can help. With examples of decorators, caching, and other tools, it highlights ways to make your code cleaner, faster, and easier to maintain.
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High-fives from Vik, Celeste, Anna P, Anna S, Anishta, Bruno, Elena, Mike, Daniel, and Brayan.